--- license: apache-2.0 datasets: - peteromallet/InScene-Dataset base_model: - black-forest-labs/FLUX.1-Kontext-dev tags: - image - editing - lora - diffusers pipeline_tag: image-to-image --- # InScene: Flux.1-Kontext.dev LoRA ## Model Description **InScene** is a LoRA for Flux.Kontext.dev that's designed to generate images that maintain scene consistency with a source image. It is trained on top of Flux.1-Kontext.dev. The primary use case is to generate variations of a shot while keeping the background and overall environment, characters, and styles the same: ![samples.png](samples.png) ## How to Use To get the best results, start your prompt with the phrase: `Make a shot in the same scene of ` And describe your new image. For example: `Make a shot in the same scene of the car up very close to the camera with the driver smiling manically.` ### Strengths & Weaknesses The model excels at: - Generating realistic shots that are consistent with the original scene. - Handling most common photographic and artistic styles. The model may struggle with: - Action-oriented prompts (e.g., "punching", "running"). - Uncommon or highly abstract styles. ## Training Data The `InScene` LoRA was trained on 394 image pairs. This dataset was created by extracting and enriching frames from the WebVid dataset. You can find the public dataset used for training here: [https://huggingface.co/datasets/peteromallet/InScene-Dataset](https://huggingface.co/datasets/peteromallet/InScene-Dataset)